Computer Architecture: Pipelined and Parallel Processor Design
Computer Architecture: Pipelined and Parallel Processor Design
Computer architecture: a quantitative approach
Computer architecture: a quantitative approach
A Performance Study of BDD-Based Model Checking
FMCAD '98 Proceedings of the Second International Conference on Formal Methods in Computer-Aided Design
Compressed caching and modern virtual memory simulation
Compressed caching and modern virtual memory simulation
Adaptive Compressed Caching: Design and Implementation
SBAC-PAD '03 Proceedings of the 15th Symposium on Computer Architecture and High Performance Computing
Adaptive Cache Compression for High-Performance Processors
Proceedings of the 31st annual international symposium on Computer architecture
Effectiveness of simple memory models for performance prediction
ISPASS '04 Proceedings of the 2004 IEEE International Symposium on Performance Analysis of Systems and Software
The case for compressed caching in virtual memory systems
ATEC '99 Proceedings of the annual conference on USENIX Annual Technical Conference
Improving application performance through swap compression
ATEC '99 Proceedings of the annual conference on USENIX Annual Technical Conference
Supporting Huge Address Spaces in a Virtual Machine for Java on a Cluster
Languages and Compilers for Parallel Computing
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Many applications with large data spaces that cannot run on a typical workstation (due to page faults) call for techniques to expand the effective memory size. One such technique is memory compression.Understanding what applications under what conditions can benefit from main memory compression is complicated due to various tradeoffs and the dynamic characteristics of applications. For instance, a large area to store compressed data increases the effective memory size considerably but also decreases the amount of memory that can hold uncompressed data.This paper presents an analytical model that states the conditions for a compressed-memory system to yield performance improvements. Parameters of the model are the compression algorithm efficiency, the amount of data being compressed, and the application memory access pattern. Such a model can be used by an operating system to compute the size of the compressed-memory level that can improve an application's performance.